IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve. appeared first on IBM Blog.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

Domino Data Lab

JULY 28, 2021

Through a marriage of traditional statistics with fast-paced, code-first computer science doctrine and business acumen, data science teams can solve problems with more accuracy and precision than ever before, especially when combined with soft skills in creativity and communication. Math and Statistics Expertise.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

IBM Big Data Hub

NOVEMBER 29, 2023

Creating synthetic test data to expedite testing, optimization and validation of new applications and features. In other words, a differentially private synthetic dataset still reflects the statistical properties of your real dataset. You can combine this data with real datasets to improve AI model training and predictive accuracy.

Metrics 89

Metrics Machine Learning Risk Statistics 89

Occam's Razor

MARCH 30, 2017

People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Most Deep Learning methods involve artificial neural networks, modeling how our bran works. Here’s the higher-order-bit….

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. MLOps and IBM Watsonx.ai

Data Science 59

Data Science Machine Learning Cost-Benefit Deep Learning 59

Domino Data Lab

JULY 28, 2021

Data science is a field at the convergence of statistics, computer science and business. In this article, take a deep dive into data science and how Domino’s Enterprise MLOps platform allows you to scale data science in your business. In fact, deep learning was first described theoretically in 1943.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

IBM Big Data Hub

APRIL 18, 2024

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. Building an in-house team with AI, deep learning , machine learning (ML) and data science skills is a strategic move.

Cost-Benefit 97

Cost-Benefit Modeling Manufacturing Interactive 97

bridgei2i

OCTOBER 7, 2020

To get a perspective on evolving trends in insurance in the post-COVID world, read BRIDGEi2i’s blog here. Importance of capturing market data for optimized pricing models. At the final stages of pricing optimization and quote generation, automation can recommend rates along with application & risk summary. click here.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control. This blog post motivates this problem more fully, and discusses monotonic splines and lattices as a solution. PLFs have two useful properties that we take advantage of.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Smarten

APRIL 19, 2024

Benefits include customized and optimized models, data, parameters and tuning. Price and bundling optimization, demand pricing, and other variables will be included to provide the best options, prices and responses and to personalize the approach and present results for data analysis and for end users.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Domino Data Lab

APRIL 21, 2021

In contrast, the decision tree classifies observations based on attribute splits learned from the statistical properties of the training data. Machine Learning-based detection – using statistical learning is another approach that is gaining popularity, mostly because it is less laborious. describe().

Statistics 69

Statistics Machine Learning Modeling Metrics 69

Cloudera

NOVEMBER 3, 2021

Thanks to pioneers like Andrew NG and Fei-Fei Li, GPUs have made headlines for performing particularly well with deep learning techniques. Today, deep learning and GPUs are practically synonymous. While deep learning is an excellent use of the processing power of a graphics card, it is not the only use.

Deep Learning 115

Deep Learning Machine Learning Data Science Cost-Benefit 115

IBM Big Data Hub

DECEMBER 20, 2023

ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. A semi-supervised learning model might use unsupervised learning to identify data clusters and then use supervised learning to label the clusters.

Machine Learning 83

Machine Learning Modeling Deep Learning Predictive Modeling 83

Domino Data Lab

JULY 22, 2019

This blog post provides a concise session summary, a video, and a written transcript. He was saying this doesn’t belong just in statistics. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. Session Summary. Tukey did this paper.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

datapine

NOVEMBER 19, 2019

AI refers to the autonomous intelligent behavior of software or machines that have a human-like ability to make decisions and to improve over time by learning from experience. Currently, popular approaches include statistical methods, computational intelligence, and traditional symbolic AI.

Technology 279

Technology Internet of Things IT IoT 279

Domino Data Lab

MAY 8, 2019

Other good related papers include: “ Towards A Rigorous Science of Interpretable Machine Learning ”. Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Smart Data Collective

NOVEMBER 9, 2022

There are a number of great applications of machine learning. One of the biggest benefits is testing processes for optimal effectiveness. The main purpose of machine learning is to partially or completely replace manual testing. Machine learning is used in many industries. It is headquartered in Silicon Valley.

Machine Learning 97

Machine Learning Testing Cost-Benefit Data-driven 97